Epstein Secrets

reinforcement learning mode, to learn small programs that will guide the virtual parrot in achieving its goals (where its goals are managed via the OpenPsi motivational system inside OpenCog, loosely inspired by Joscha Bach's MicroPsi system). • Use of ECAN to learn associational relationships between

e more attention. Action selection will be done via OpenPsi according to the Psi model, roughly similarly to how it is done in Joscha Bach's (2012) MicroPsi model. This means that actions will be chosen based on the probabilities with which they are estimated to lead to achievement of the currently high-

reinforcement learning mode, to learn small programs that will guide the virtual parrot in achieving its goals (where its goals are managed via the OpenPsi motivational system inside OpenCog, loosely inspired by Joscha Bach's MicroPsi system). • Use of ECAN to learn associational relationships between

e more attention. Action selection will be done via OpenPsi according to the Psi model, roughly similarly to how it is done in Joscha Bach's (2012) MicroPsi model. This means that actions will be chosen based on the probabilities with which they are estimated to lead to achievement of the currently high-

that recognizes patterns in the hierarchies and passes them to the Atomspace; and imprints patterns from the Atomspace on the hierarchies); and also OpenPsi, a special dynam- ical framework for choosing actions based on motivations. Above the Atomspace we have a host of cognitive processes, which act on

ut on the big- picture level the main difference lies in the way the cognitive synergy principle is pursued in the two different approaches. Psi and MicroPsi rely on very simple learning algorithms that are closely tied to the "quad" neurosymbolic knowledge representation, and hence interoperate in a fai

(that recognizes patterns in the hierarchies and passes them to the Atomspace; and imprints patterns from the Atomspace on the hierarchies); and also OpenPsi, a special dynam- ical framework for choosing actions based on motivations. Above the Atomspace we have a host of cognitive processes, which act on t

but on the big- picture level the main difference lies in the way the cognitive synergy principle is pursued in the two different approaches. Psi and MicroPsi rely on very simple learning algorithms that are closely tied to the “quad” neurosymbolic knowledge representation, and hence interoperate in a fairl